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use this formalisation to encode our STV algorithm on encrypted ballots. This approach aims to ensure both the correctness and privacy of the tallying process, paving the way for verifiable and secure
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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simultaneously, useful for printing functional devices. Discovering the interactions of these materials and how to leverage this advanced manufacturing process will open new opportunities: devices with variable
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world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, biotechnology, physics, and materials science. PhD project description: Responsive 3D
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motivated applicant to undertake an original and applied programme of research linked to ongoing work led nationally by the Chartered Institute for the Management of Sport and Physical Activity (CIMSPA
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complex input. For instance, in physics-informed ML, in addition to data examples used by a standard ML setup, domain knowledge serves as an additional input. It can be in an explicit form of rigorous
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a collaborative studentship between the University of Edinburgh and the National Physics Laboratory (https://www.npl.co.uk/ ). The position will be registered and hosted at the University of Edinburgh
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considered to be self-funded students for the purposes of admission. Applicants should have (or expect to obtain by the start date) at least a first class degree in an Physics, Mathematics, Electrical
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Arrangements: This is an in-person role based in Durham, requiring physical presence on campus and regular travel to partner schools in the region to support intervention delivery. The part-time hours (10 per
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under-represented backgrounds Adjustments available to support candidates with physical disabilities or neurodivergence You’ll be a good fit if you: Have a background in Biochemistry, biomedical sciences